Operational research techniques are to analyze the problem of decision making such as good site for plant , whether to open a new storehouse, etc. It also helps in assortment of cost-effective means of transportation, jobs sequencing, production scheduling, replacement of old machinery, etc. Decision making is the process of making choices by identifying a decision, gathering information, and assessing alternative resolutions. Using a step-by-step decision-making process can help you make more deliberate, thoughtful decisions by organizing relevant information and defining alternatives.

1. Presentation on
DECISION MAKING

2. INTRODUCTION
• Decision making is a key managerial responsibility
• Decision making is a choice amongst alternatives
• Steps involved:
– Defining the problem
– Setting the objectives
– Collecting data
– Analyzing data/Generating alternatives
– Evaluate and select the best alternative

3. TYPES OF DECISIONS
Based on Simon’s idea decisions can be:
• Structured decisions which are for routine and
typically repetitive problems for which standard
solution method exists
• Unstructured decisions which are for fuzzy,
complex problems for which there are no cut-
and-dried solution methods
• Semi structured decisions which are for problems
having some structured elements and some
unstructured elements

4. DECISION TABLE
• Possible for only structured/programmed
decisions
• It is a non-graphical way of representing the
steps involved in making a decision
• It is usually easier to construct a decision tree
first from the description of how a decision is
made and then create the decision table
• It consists of some conditions, rules and
actions

5. • Conditions – these are created from each decision
question. Only one possible answer from each question
is selected for use in the table. Each answer
corresponds to one of each pair of branches in the
tree.
• Actions – these are the final outcomes of the decision
process and are the branch ends or outcomes of the
decision tree
• Rules – these give the combinations of conditions that
lead to the final actions. Y (for Yes) and N (for No)
characters in the table normally indicate which
combinations of conditions are allowed

6. Discounting policy of a phone card company

7. DECISION TREES
• A decision tree is a graphical way of representing the steps
involved in making a decision.
• A user can look at a decision tree that describes a decision
process they use and identify any errors in the diagram.
• Each horizontal ‘branch’ of the tree represents the result of
a decision or a series of decisions.
• The ‘roots’ where the branches join are the decision points
– each point represents a separate decision, a question that
much be answered.
• Decision points typically have two or three branches.
• At the ends of the branches are the outcomes of the
decision process

8. The general arrangement of a decision tree is as shown below

9. Decision tree to describes the emergency sequence

10. A Library Membership Software(LMS) should support the following
three options: new member, renewal, and cancel membership. When
the new member option is selected, the software should ask for the
member’s name, address, and phone number. If proper information is
entered, the software should create a membership record for the new
member and print a bill for the annual membership charge and the
security deposit payable. If the renewal option is chosen, the LMS
should ask for the member’s name and the membership number. If the
member details entered are valid, then the membership expiry date in
the membership record should be updated and the annual
membership charge payable by the member should be printed. If the
cancel membership option is selected and the name of a valid member
is entered, then the membership is cancelled, a cheque for the balance
amount due to the member is printed and his membership record is
deleted.

11. Decision tree for LMS
Valid selection?
Yes
No
New member
Renewal
Cancel membership
• Ask for member’s name, address, phone number
• Create membership record
• Print bill
• Display error message
• Ask for membership details
• Update expiry date
• Print bill
• Ask for membership details
• Delete membership record
• Print cheque

12. Decision table for LMS

13. SIMON’S DECISION MAKING PROCESS
Simon describes the decision making process with a
four phase process of:
• Intelligence phase: searching for conditions that
call for decisions
• Design phase: inventing, developing and
analyzing possible course of action
• Choice phase: selecting a course of action from
those available
• Implementation phase: once a proposed solution
seems reasonable execution starts and result is
either a success or failure

14. Intelligence Phase
Problem Identification
Problem Classification
Problem Decomposition
Problem Ownership
Design Phase
Formulate a model
Set criteria for choice
Search for alternatives
Predict and measure outcomes
Choice Phase
Solution to the model
Selection of best alternative
Plan for implementation
Implementation
Phase
Failure
Problem Statement
Alternatives
Solution
Reality
Success
Validation of the model
Verification, testing of
Proposed solution
Simplification
Assumptions

15. THE INTELLIGENCE PHASE
• Problem (or opportunity) identification
– Begins with the identification of organization goals
and objectives related to an issue of concern and
determination of whether they are being met
– Determine whether a problem exists, identify its
symptoms, determine its magnitude and explicitly
define it

16. • Problem classification
– It is the conceptualization of a problem in an
attempt to place it in a definable category
– It helps in leading to a standard solution approach
– Ex.
• Classifying according to the degree of
structuredness evident in the problem

17. • Problem decomposition
– Many complex problems can be divided into sub-
problems
– Solving these simpler sub-problems helps in
solving the complex problem
• Problem ownership
– It is important to understand whether the
problem is a controllable or uncontrollable factor
and if organization has the ability to solve it

18. THE DESIGN PHASE
• The design phase involves finding and
analyzing possible course of action
• These include understanding the problem and
testing solutions for feasibility
• A model of the decision making problem is
constructed, tested and validated

19. • Formulate a model
– Modeling involves conceptualization of the
problem and its abstraction to quantitative and/or
qualitative forms
Uncontrollable
Variables
Decision Variables
Mathematical
Relationships
Result Variables
GENERAL STRUCTURE OF A QUANTITATIVE MODEL

20. • Set criteria for choice
– Selection of a principle of choice describes the
acceptability of a solution approach
• Search for alternatives
– Generating alternatives is a lengthy process that
involves searching and creativity
– It takes time and costs money
– It is important to decide when to stop generating
alternatives

21. • Predict and measure outcomes
– To evaluate and compare alternatives, it is
necessary to predict the future outcome f each
proposed alternative
– It is done under three broad categories:
• Decision making under certainty
• Decision making under risk
• Decision making under uncertainty

23. THE CHOICE PHASE
The choice phase is the one in which the actual
decision is made, i.e., the commitment to follow
a certain course of action is made. The boundary
between the design and choice phase is unclear
as one can jump frequently between this two
phases. It includes,
• Solution to the model
• Selection of best alternative(s)
• Plan for implementation

25. GOAL SEEKING ANALYSIS

27. THE IMPLEMENTATION PHASE
• The implementation phase is the final stage of
the decision making process
• It is concerned with implementing and
monitoring
• The role of the system is feedback and
assessment

28. Objective Setting
Information
Gathering
Generation of
Alternatives
Evaluation of
Alternatives
Selection of
Alternative
Implementation
Monitor and
Control
Define the problem Establish cause-effect
relationship
Impose limits
Look at short range
Look at long range
Apply qualitative aids
Translate into actions
Analyze data
Decide on boundary
condition
Gather data
Decide on feasible
alternatives
Quantify and measure
against objectives
Decide on strengths
and weaknesses
Decide alternative

29. MASSIE’S DECISION MAKING MODEL
• It is a five stage procedure as follows:
1. Understand situation
2. Diagnose and define problem
3. Find alternatives
4. Select action
5. Secure acceptance of decision

30. DSS
DSS is a computer based support system for
processing data to aid the management in
decision making.

31. CAPABILITIES OF DSS
• Semi structured programs
• For managers at different levels
• For groups and individuals
• Interdependent/Sequential decisions
• Supports intelligence, design, choice phase
• Adaptability and flexibility
• Interactive ease of use
• Ease of construction
• Modelling and analysis

32. COMPONENTS OF DSS
• Data management subsystem
– DSS database, DBMS, data directory
• Model management subsystem
– Model base, MBMS, model directory
• Knowledge-based management subsystem
– Intelligent system, KBES
• User interface subsystem
– Dialog, UIMS, GUI

33. DSS CLASSIFICATIONS
• Text oriented DSS
• Database oriented DSS
• Spreadsheet oriented DSS
• Solver oriented DSS
• Rule oriented DSS
• Compound DSS
• Intelligent DSS

34. DSS APPLICATIONS
• Market planning and research
– DSS applications include pricing decisions for each
customer, forecasting, termination or expansion and
customer satisfaction
• Operation and strategic planning
– DSS is used to support both short-term and strategic
planning for monitoring, analyzing and reporting on
the market trends
• Sales support
– DSS helps by generating daily sales summaries

35. ACTIVITIES OF BUSINESS INTELLIGENCE
Data
sources
Data
warehouse
Results
Visualization
OLAP
Decision
support
Data mining
Visualization

36. CHARACTERISTICS OF GROUP WORK
• A group performs a task, sometimes decision
making, sometimes not
• Group members may be located in different places
• Group members may work at different times
• Group members may work for the same or for
different organizations
• The group can be permanent or temporary
• The group can be at any managerial level or span
levels

37. • There can be synergy or conflict in group work
• There can be gains/losses in productivity from group
work
• The task might have to be accomplished very quickly
• It may be impossible for all members to meet in one
place
• Some of the data needed may be located in sources
external to the organization
• The expertise of non-team members may be needed

38. COMMUNICATION SUPPORT
• Communication is a vital element for decision support
• Without communication there is no collaboration
• Groups of decision makers must communicate,
collaborate and negotiate in their work
• Effective e-commerce is possible only via modern
communication technologies
• Modern information technologies provide inexpensive,
fast, capable and reliable means of supporting
communication
• Collaborative technologies like EMS(electronic meeting
systems) and electronic conferencing systems and
services helps in connecting decision makers

39. TIME/PLACE COMMUNICATION
FRAMEWORK
Same Time Different Time
Same Place
• GSS in a decision room
• Web-based GSS
• Multimedia
presentation systems
• Whiteboard
• Document sharing
• GSS in a decision room
• web=-based GSS
• Workflow management
systems
• Document sharing
• E-mail, V-mail
Different Place
• Web-based GSS
• Whiteboard
• Document sharing
• Video conferencing
• Audio conferencing
• Computer conferencing
• E-mail, V-mail
• Web-based GSS
• Whiteboard
• E-mail, V-mail
• Workflow management
systems
• Document sharing
• Computer conferencing
with memory

40. KNOWLEDGE MANAGEMENT
• It is a process that helps organizations identify, select,
organize, disseminate and transfer important
information and expertise that are part of the
organizational memory that typically resides within the
organization in an unstructured manner
• This enables effective and efficient problem solving,
dynamic learning, strategic planning and decision
making
• It thus focuses on identifying knowledge, explicating it
in a way so that it can be shared in a formal manner
and thus reusing it

41. IMPORTANCE OF MANAGING
KNOWLEDGE
• Intellectual capital is a firm’s only appreciable asset.
Most assets depreciate with time.
• Knowledge work is increasing
• Employees with the most intellectual capital have
become volunteers
• Many managers ignore intellectual capital and lose out
on the benefits of its capture and use
• Employees with the most intellectual capital are often
the least appreciated
• Many current investment in intellectual capital are
misfocussed

42. FEATURES OF KNOWLEDGE
MANAGEMENT SYSTEM
• Creating a knowledge culture
• Capturing knowledge
• Knowledge generation
• Knowledge explication(and digitization)
• Knowledge sharing and reuse
• Knowledge renewal

43. Knowledge management system processes are
designed to manage
• Knowledge creation through learning
• Knowledge capture and explication
• Knowledge sharing and communication
• Knowledge access
• Knowledge use and reuse
• Knowledge archiving

44. THE KNOWLEDGE MANAGEMENT CYCLE
Create
knowledge
Capture
knowledge
Refine
knowledge
Store
knowledge
Manage
knowledge
Disseminate
knowledge

45. IMPLEMENTING KNOWLEDGE MANAGEMENT
1. Identify the problem by identifying knowledge segments
2. Prepare for change in terms of business efforts and
operation
3. Create the team responsible for implementing a pilot
project
4. Map out the knowledge by identifying what it is, where it
is, who has it and who needs it
5. Create a feedback mechanism indicating how the system
is used and report any difficulties
6. Define the building blocks for a knowledge management
system
7. Integrate existing information systems to contribute and
capture knowledge in an appropriate format

46. Data, Information and Knowledge
DATA
INFORMATION
KNOWLEDGE
Processed Relevant and
actionable
Relevant and actionable data
Knowledge management transforms data and/or information
into actionable knowledge in a format that when it is made
available can be utilized effectively and efficiently throughout an
organization

47. TACIT AND EXPLICIT KNOWLEDGE
• Tacit knowledge is in the domain of subjective,
cognitive and experiential learning
• Explicit knowledge deals more with objective,
rational and technical knowledge(data, policies,
procedures, software, documents)
• Knowledge management transfers the tacit
knowledge in individuals to value processes that lead
to innovation, knowledge creation and
replenishment of the organization’

48. Explicit
Knowledge
Tacit
Knowledge
Core competencies
of the organization
Process of explication may generate
New tacit knowledge
Convert tacit knowledge to
articulated and measurable
explicit knowledge
Policies, patents,
decisions, strategies etc.
Expertise, know-how,
Ideas, organization
culture, values etc.

49. MSS
• Modeling is a key element in most DSS and a
necessity in a model-based DSS
• Management support systems(MSS) are
collections of computerized technologies used to
support managerial tasks in general and decision
making in particular
• MSS refers to application of any technology,
either as an independent tool or in combination
with other information technologies

50. IMPLEMENTING MSS
• MSS technology implementation is complex
because these systems are not merely
information systems that collect, manipulate and
distribute information; rather they are linked to
tasks that may significantly change the manner in
which organizations operate
• MSS implementation is an ongoing process that
occurs during the entire development of the
system, through the feasibility study, system
analysis and design, programming, training,
conversion and installation

51. ISSUES OF IMPLEMENTATION
• Technical factors
Technical issues can be classified in two categories:
– Technical constraints which results mainly from
the limitations of available technology. It
disappears when new technology are developed
– Technical problems which are not result of the
technology but are caused by other factors such
as scarcity of resources. It can be solved by
increasing the available resources

52. • Behavioral factors
– The way people perceive these systems and how they
behave in accepting them
– User resistance is a major behavioral factor
– Reasons that employees resist new systems:
• Change in job content
• Loss of status
• Change in interpersonal relationships
• Loss of power
• Change in decision making approach
• Uncertainty/unfamiliarity/misinformation
• Job security

53. • Process factors
– Top management support for continuous financial
support to maintain the systems
– Management and user commitment
– Institutionalization through which an MSS
becomes incorporated
• User involvement
– Participation in the system development process
by users is a necessary condition

54. • Organizational factors
– Competence skills of the MSS team
– Adequacy of resources
– Organizational politics
• Values and ethics
– Prime concerns are goals of the project, process
and possible impact on other systems
• External environment
– Includes legal, social, economic, political etc.

55. IMPLEMENTATION STRATEGIES FOR
DSS
Implementation strategies for DSS can be
divided into four major categories:
• Divide the project into manageable pieces
• Keep the solution simple
• Develop a satisfactory support base
• Meet user needs and institutionalize the
system

56. EXPERT SYSTEM IMPLEMENTATION
• QUALITY OF THE SYSTEM
– The ES should be developed to fulfill a recognized
need
– The ES should be easy to use even by a novice
– The ES should be able to increase the expertise of
the user
– The ES should have explorative capabilities

57. – The program should be capable to respond to
simple questions
– The system should be capable of learning new
knowledge (i.e., the system should be able to ask
questions to gain additional information)
– The program knowledge should be easily modified
(i.e., add, delete, and changed)

58. • COOPERATION OF THE EXPERTS
– For an ES to be successfully implemented it must
give good advice. Such advice depends, most of
all, on the cooperation of the domain expert
• CONDITIONS THAT JUSTIFY THE NEEDS FOR A
PARTICULAR ES
– An expert is not always available or is expensive
– Decisions must be made under pressure or
missing even a single factor could be disastrous

59. – There is rapid employee turnover, resulting in a
constant need to train new workers. Such training
is costly and time-consuming
– A huge amount of data must be shifted through

60. SYSTEM INTEGRATION
• Integration of computer based systems means
that the systems are merged into one facility
rather than having separate hardware,
software, and communications for each
independent systems.
• Integration can be at the development tools
level or at the application system level

61. TYPES OF INTEGRATION
There are two general types:
Functional integration implies that different
support functions are provided as a single system. A
user can access the appropriate facilities through a
single, consistent interface and can switch from one
task to another and back again
Physical integration refers to packaging of the
hardware, software, and communication features
required to accomplish functional integration

62. WHY INTEGRATE?
• Enhancements of basic tools
• Increasing the capabilities of the application
– Benefits that each technology provides to the
other
– Improvements in both the process and the
outcome
– It results in combining the strengths of each
individual technique

63. PROBLEMS AND ISSUES IN
INTEGRATION
• Need for integration
• Justification and cost-benefit analysis
• Architecture of integration
• People problems
• Finding appropriate builders
• Attitudes of employees in the information system
department
• Development progress
• Organizational impacts
• Data structure issues
• Data issues
• Connectivity

64. OPERATIONS RESEARCH
• Operations research(OR) is a quantitative
approach to decision making
• Mostly used as a support for structure
decisions
• Characteristics of OR:
– Systems approach
– Analytical approach
– Interdisciplinary approach
– Deals with real world problems

65. OR METHODOLOGY
The steps involved are:
Problem Identification
Need analysis
Cause and effect analysis
Model Construction
Data collection
Model design
Model evaluation

66. Experimentation
Feasibility analysis
Optimality analysis
Adaptivity analysis
Implementation
Management approval
Test operations
Full implementation
Evaluation

67. CAUSE-EFFECT DIAGRAM
Problem
Causes
Date
Effects